Collaborative Research: SaTC: CORE: Large: Privacy-Preserving Abuse Prevention for Encrypted Communications Platforms

协作研究:SaTC:核心:大型:加密通信平台的隐私保护滥用预防

基本信息

  • 批准号:
    2120497
  • 负责人:
  • 金额:
    $ 37.14万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-08-01 至 2026-07-31
  • 项目状态:
    未结题

项目摘要

This project will address the immense challenge of mitigating abuse in communication services where interactions between the parties are private and fully encrypted. Such services have become popular for individual and group communications, and their security features help protect individual privacy and rights. But these platforms are also used for harmful and illegal purposes such as organizing violent activities or sharing child sexual abuse materials. In addition, users on these platforms are subject to abuse such as hate, harassment, and misinformation. The encryption used by such services makes detecting and blocking harmful content extremely difficult. This work will develop new trust and safety approaches to enable secure and trustworthy communications that preserve privacy while mitigating abuses. The project will aim to provide (1) technical advances in developing novel cryptographic tools and techniques to support mitigation of abuse; (2) human-centered advances in understanding perceptions and expectations of privacy and abuse mitigation, as well as creating novel designs for individual and community interactions; and (3) legal, policy, and regulatory advances to support and enable these abuse-mitigating features.The research effort is organized around two overlapping thrusts: algorithmic-driven approaches and community-driven approaches. The algorithmic approaches will focus on developing better cryptographic tools for privacy-aware abuse detection in encrypted settings, such as detection of viral, fast-spreading content. These designs will be informed by a human-centered approach to understanding people's privacy expectations, and supported by legal analyses that ensure tools are consistent with applicable privacy and content-moderation laws. In the second thrust, the community approaches will focus on providing communities with the tools they need to address abuse challenges in encrypted settings. Given the challenges and pitfalls of centralized approaches for abuse mitigation, the project will explore building distributed capabilities to support communities and groups on these platforms. An importantly ingredient is working with communities and community moderators to understand their needs, as well as guide design of legal and policy frameworks to support new approaches.Taken together, this project will address the challenge of abuse mitigation on encrypted platforms, while preserving privacy protections for individuals and communities. It will especially consider the perspectives of individuals and communities most in need of privacy and abuse protection. The work, if successful, should fuel new innovations in the design of encrypted messaging platforms, and in basic research in cryptography, human-centered design, and Internet law.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该项目将解决减少通信服务滥用的巨大挑战,其中各方之间的交互是私密且完全加密的。此类服务已在个人和团体通信中变得流行,其安全功能有助于保护个人隐私和权利。但这些平台也被用于有害和非法目的,例如组织暴力活动或分享儿童性虐待材料。此外,这些平台上的用户还容易受到仇恨、骚扰和错误信息等虐待。此类服务使用的加密使得检测和阻止有害内容变得极其困难。这项工作将开发新的信任和安全方法,以实现安全且值得信赖的通信,在保护隐私的同时减少滥用行为。该项目旨在提供 (1) 开发新型加密工具和技术方面的技术进步,以支持减轻滥用行为; (2) 在理解隐私和滥用缓解的看法和期望方面取得以人为本的进步,并为个人和社区互动创造新颖的设计; (3) 法律、政策和监管方面的进步,以支持和实现这些减少滥用的功能。研究工作围绕两个重叠的主旨进行组织:算法驱动的方法和社区驱动的方法。 算法方法将侧重于开发更好的加密工具,用于加密环境中的隐私意识滥用检测,例如检测病毒式、快速传播的内容。这些设计将以以人为本的方法来了解人们的隐私期望,并得到法律分析的支持,以确保工具符合适用的隐私和内容审核法律。在第二个重点中,社区方法将侧重于为社区提供解决加密环境中滥用挑战所需的工具。考虑到集中式缓解滥用方法的挑战和陷阱,该项目将探索构建分布式功能来支持这些平台上的社区和团体。一个重要的组成部分是与社区和社区管理员合作,了解他们的需求,并指导法律和政策框架的设计以支持新方法。总之,该项目将解决加密平台上滥用缓解的挑战,同时保留隐私保护对于个人和社区。它将特别考虑最需要隐私和滥用保护的个人和社区的观点。这项工作如果成功,将推动加密消息平台的设计以及密码学、以人为本的设计和互联网法的基础研究方面的新创新。该奖项反映了 NSF 的法定使命,并通过使用评估结果被认为值得支持。基金会的智力价值和更广泛的影响审查标准。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets
肤浅:研究计算机视觉基准数据集肤色注释的主观性
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Amy Zhang其他文献

Circularity and Enclosures: Metabolizing Waste with the Black Soldier Fly
循环性和外壳:黑水虻代谢废物
  • DOI:
    10.14506/ca35.1.08
  • 发表时间:
    2020-02-01
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    Amy Zhang
  • 通讯作者:
    Amy Zhang
Mechanical Trap Surface-Enhanced Raman Spectroscopy for Three-Dimensional Surface Molecular Imaging of Single Live Cells.
用于单个活细胞三维表面分子成像的机械陷阱表面增强拉曼光谱。
  • DOI:
    10.1002/anie.201700695
  • 发表时间:
    2017-03-27
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Q. Jin;Ming Li;Beril Polat;S. Paidi;A. Dai;Amy Zhang;Jayson V. Pagaduan;I. Barman;D. Gracias
  • 通讯作者:
    D. Gracias
Causal Transformers: Improving the Robustness on Spurious Correlations
因果变换器:提高虚假相关性的鲁棒性
  • DOI:
  • 发表时间:
    2024-09-14
  • 期刊:
  • 影响因子:
    0
  • 作者:
    David Krueger;Ethan Caballero;Joern;Amy Zhang;Jonathan Binas;Dinghuai Zhang;Yinhan Liu;Myle Ott;Naman Goyal;Jingfei Du;M;ar Joshi;ar;Danqi Chen;Omer Levy;Mike Lewis;Ze Liu;Yutong Lin;Yue Cao;Han Hu;Yixuan Wei;Jiasen Lu;Dhruv Batra;Devi Parikh;Tom McCoy;Ellie Pavlick;Tal Linzen;Nikita Nangia;Adina Williams;A. Lazaridou;Ankur P. Parikh;Oscar Täckström;Dipanjan Das;Jeffrey Pennington;R. Socher;Lihua Qian;Hao Zhou;Yu Bao;Mingxuan Wang;Lin;Alec Radford;Jeffrey Wu;R. Child;D. Luan;Chitwan Saharia;William Chan;Saurabh Saxena;Rico Sennrich;B. Haddow;Ale;ra Birch;ra
  • 通讯作者:
    ra
Confidence-aware 3D Gaze Estimation and Evaluation Metric
置信感知 3D 凝视估计和评估指标
  • DOI:
    10.48550/arxiv.2303.10062
  • 发表时间:
    2023-03-17
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Qiaojie Zheng;Jiucai Zhang;Amy Zhang;Xiaoli Zhang
  • 通讯作者:
    Xiaoli Zhang
Comparing binary & ordinal definitions of urinary & stool continence outcomes: Data from the National Spina Bifida Patient Registry.
比较二进制
  • DOI:
    10.1016/j.jpurol.2024.01.029
  • 发表时间:
    2024-02-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Kelly;Tiebin Liu;J. Routh;H. Castillo;Stacy T. Tanaka;Kathryn A. Smith;L. Krach;Amy Zhang;Eileen Sherburne;Jonathan Castillo;Joseph David;John S. Wiener
  • 通讯作者:
    John S. Wiener

Amy Zhang的其他文献

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{{ truncateString('Amy Zhang', 18)}}的其他基金

CAREER: Dual Reinforcement Learning: A Unifying Framework with Guarantees
职业:双重强化学习:有保证的统一框架
  • 批准号:
    2340651
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
CAREER: Tools for User and Community-Led Social Media Curation
职业:用户和社区主导的社交媒体管理工具
  • 批准号:
    2236618
  • 财政年份:
    2023
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
Collaborative Research: DASS: Transitioning open-source software projects to accountable community governance
合作研究:DASS:将开源软件项目转变为负责任的社区治理
  • 批准号:
    2217653
  • 财政年份:
    2022
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317232
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338302
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Using Intelligent Conversational Agents to Empower Adolescents to be Resilient Against Cybergrooming
合作研究:SaTC:核心:中:使用智能会话代理使青少年能够抵御网络诱骗
  • 批准号:
    2330940
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Using Intelligent Conversational Agents to Empower Adolescents to be Resilient Against Cybergrooming
合作研究:SaTC:核心:中:使用智能会话代理使青少年能够抵御网络诱骗
  • 批准号:
    2330941
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317233
  • 财政年份:
    2024
  • 资助金额:
    $ 37.14万
  • 项目类别:
    Continuing Grant
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